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RESEARCH ARTICLES
◥
PAL EO ECOLO GY
Abrupt warming events drove
Late Pleistocene Holarctic
megafaunal turnover
Alan Cooper,
1
*Chris Turney,
2
*Konrad A. Hughen,
3
Barry W. Brook,
4,5
H. Gregory McDonald,
6
Corey J. A. Bradshaw
4
The mechanisms of Late Pleistocene megafauna extinctions remain fiercely contested,
with human impact or climate change cited as principal drivers.We compared ancient DNA
and radiocarbon data from 31 detailed time series of regional megafaunal extinctions and
replacements over the past 56,000 years with standard and new combined records of
Northern Hemisphere climate in the Late Pleistocene. Unexpectedly, rapid climate changes
associated with interstadial warming events are strongly associated with the regional
replacement or extinction of major genetic clades or species of megafauna. The presence
of many cryptic biotic transitions before the Pleistocene/Holocene boundary revealed by
ancient DNA confirms the importance of climate change in megafaunal population
extinctions and suggests that metapopulation structures necessary to survive such
repeated and rapid climatic shifts were susceptible to human impacts.
The debate surrounding the causes of the ex-
tinctions of megafaunal species (terrestrial
taxa with adults >45 kg), which occurred
during the last glacial period (~110,000 to
11,650 calendar years ago; 110 to 11.65 ka) in
the Late Pleistocene, has continued for over two
centuries, since Cuvier first identified the mam-
moth and giant ground sloth (1–5). Although hu-
man activity as a result of hunting (“overkill”)
and/or habitat modification and fragmentation are
often cited as the principal driving force (1,6–8),
the diversity of extinction patterns observed on
different continents has led to increasing recog-
nition of the potential synergistic role of climate
change (1–4,9). A major confounding factor in
thedebatehasbeenthecoincidentLatePleistocene
increase in human population size and dispersal
into previously uninhabited areas, such as the
New World, potentially exacerbating other eco-
logical impacts.
Traditionally, a key argument against the po-
tential role of climate-change impacts has been
the paucity of identified extinction events during
either previous glacial cycles or the many well-
defined, climatic shifts recorded during the last
glacial period (3,4), including the Last Glacial
Maximum (LGM; ~23 to 19 ka) (Fig. 1). However,
the lack of suitably resolved records of climate
change and radiocarbon calibration on a com-
mon time scale makes such interpretations par-
ticularly challenging. The debate has also been
constrained by the heavy reliance on fossil mor-
phological evidence, precluding the identification
of major genetic transitions or population-level
turnovers. Recent work using ancient DNA (aDNA)
has shown that morphological analyses of the
Pleistocene paleontological record can have lim-
ited power to resolve species-level mammalian
taxonomy issues or detect broad-scale genetic tran-
sitions at the population level, even when species
suffer major genetic losses or almost go extinct
(10–15). Indeed, aDNA and genomic studies have
revealed a far more dynamic picture of megafaunal
population ecology, including repeated local-
ized extinctions, migrations, and replacements
(10,12–15).
The Late Pleistocene was characterized by a
series of severe and rapid climate oscillations
(regional temperature changes of up to 16°C) known
as Dansgaard-Oeschger (D-O)interstadial(warming)
events that have been identified in oceanic, ice,
and terrestrial records throughout the Northern
Hemisphere (16) (Fig. 1 and fig. S3). The millennial-
length D-O events can be bundled into semi-
regular cooling cycles with an asymmetrical
saw-tooth pattern (Bond cycles) (17)thatculminate
in massive discharges of ice into the North Atlantic,
known as Heinrich events. However, the precise
timing, magnitude, and global extent of these
events remain sufficiently uncertain to impair re-
search into the effects of such rapid and extreme
climate shifts on landscape and paleoecological
change. In particular, there has been limited analysis
of the potential relationship between rapid climate
change and major genetic transitions in wide-
spread populations, marked by local extirpations
or global extinctions of species and genetic diversity.
Megafaunal data
To investigate this, we examined all available mega-
faunal species with comprehensive radiocarbon-
dated series and plotted 31 calibrated major
megafaunal transition events (defined as geograph-
ically widespread or global extinctions, or inva-
sions, of species or major clades) that have been
detected in either genetic (13 events) or paleon-
tological (18 events) studies against the Green-
land ice core record [on the Greenland Ice Core
Chronology 2005 (GICC05) time scale] (18–20)
(Fig. 1).
The genetic and radiocarbon data reveal a tem-
porally staggered, long-term dynamic record of
major megafaunal transitions across species with
diverse ecologies and life histories. The events
were widely distributed geographically across
both Eurasia and the New World and included
periods before human invasion. Multiple events
appear to involve the rapid replacement of one
species or population by a conspecific or conge-
neric across a broad area, often making the events
undetectable in the fossil record on the basis of
morphology, and potentially even in low-resolution
genetic reconstructions of population paleode-
mography (21). These rapid replacements suggest
that putative taphonomic biases (e.g., increased
fossilization rates during either interstadials or
stadials—cold periods) are not responsible for the
apparent sudden disappearance or appearance of
genetic diversity. Furthermore, common megafau-
nal fossils, such as mammoth, appear throughout
thetimeperiodexamined(Fig.1).Theapparent
absence of extinctions during the cold conditions
of the LGM, when Northern Hemisphere ice sheets
reached their maximum volume, or to a lesser ex-
tent during the Younger Dryas stadial (11.7 to
12.7 kya; table S3) at the very end of the Pleisto-
cene, is surprising, given that these events are
commonly postulated as potential causes of mega-
faunal extinctions (3,22). Although paleontolog-
ical studies record range contractions into glacial
refugia for many species during this period (4),
it appears that, in general, cold conditions were
not an important driver for extinctions, even in
the presence of anatomically modern humans
in Europe.
The megafaunal transitions appear to be cen-
tered around D-O warming events leading up to
and then after the LGM, including a marked
cluster of events around interstadials 5 to 7 in
northern Europe (~37 to 32 ka; Fig. 1). A further
well-known cluster of extinction events occurs
during the termination of the Pleistocene (~14 to
11 ka), which has often been linked to the initial
entry of humans into the New World (~15 ka) (6–8).
However, half of the 12 extinction events in this
period occur in western Eurasia, where modern
humans arrived at least ~44 kya. Indeed, several
taxa (e.g., mammoth) go extinct on the mainland
of Eurasia considerably later than that of the
New World, despite a much longer exposure to
human hunting (3,4)(Fig.1).
RESEARCH
602 7 AUGUST 2015 •VOL 349 ISSUE 6248 sciencemag.org SCIENCE
1
Australian Centre for Ancient DNA, School of Earth and
Environmental Sciences, and Environment Institute,
University of Adelaide, Adelaide, Australia.
2
Climate Change
Research Centre and School of Biological, Earth, and
Environmental Sciences, University of New South Wales,
Sydney, Australia.
3
Woods Hole Oceanographic Institution,
Woods Hole, MA 02543, USA.
4
Environment Institute and
School of Biological Sciences, University of Adelaide,
Adelaide, Australia.
5
School of Biological Sciences, University
of Tasmania, Hobart, Australia.
6
Museum Management
Program, National Parks Service, Fort Collins, CO 80525, USA.
*Corresponding author. E-mail: alan.cooper@adelaide.edu.au
(A.C.); c.turney@unsw.edu.au (C.T.)
on August 6, 2015www.sciencemag.orgDownloaded from on August 6, 2015www.sciencemag.orgDownloaded from on August 6, 2015www.sciencemag.orgDownloaded from on August 6, 2015www.sciencemag.orgDownloaded from on August 6, 2015www.sciencemag.orgDownloaded from
Greenland-Cariaco climate time scale
A major challenge for testing whether the genetic
transitions were synchronous with D-O events is
the placement of megafaunal and climate re-
cords on a common time scale (23). Although the
Greenland ice cores (18,19) provide a detailed
record of climate change for the North Atlantic,
cumulative counting errors can exceed 2% (fig.
S1) (20), resulting in calendar time scale offsets of
up to 1000 years between Greenland D-O events
and radiocarbon-calibrated megafaunal transi-
tions (23,24). To enable detailed comparisons,
the climate and radiocarbon records should be
on the same absolute time scale, which requires
the merging of different high-resolution data
sets.Importantly,thisalsoprovidesameansto
improve the accuracy and the precision of the
chronological framework and to assess the hem-
ispheric nature of the climate shifts. One such
approach is to use the abrupt shifts at the onset
of D-O warming as tie points to correlate across
multiple climate records (25), because these events
caused widespread and rapid climate effects by
decreasing the Northern Hemisphere tempera-
ture gradient (26), resulting in a poleward migra-
tion of the Intertropical Convergence Zone (ITCZ)
and associated changes in tropical rainfall belts
(27–31). In this regard, a key record is the Ven-
ezuelan Cariaco Basin marine sequence, which
captures a climate record via shifts in the trade
winds associated with northward migration of
the ITCZ in the tropical Atlantic (20,28), along-
side a comprehensive suite of radiocarbon ages
from planktonic foraminifera in the sediment core.
The Cariaco sediments are annually laminated
during the Late Glacial and Holocene, providing
independent age control from 14.7 ka (32), before
which distinct millennial-scale variability in sedi-
mentological and geochemical proxies has been
robustly correlated with the uranium series–dated
Hulu Cave oxygen isotope ratio (d
18
O) speleothem
record (with age uncertainties < 1%) (33).
SCIENCE sciencemag.org 7 AUGUST 2015 •VOL 349 ISSUE 6248 603
4000 8000 12000 16000 20000 24000 28000 32000 36000 40000 44000 48000 52000 56000
Years Before Present
LGM
HOL GI-1 GI-2 NEA
GS-3b
GI-3
GI-4 GI-5 GI-6 GI-7 GI-8 GI-9
GI-10 GI-11
YD
GI13
onset
GI-14
onset
GI-15
onset
x mammoth New World
o mammoth Eurasia
δ
18
O
Homo sapiens
New World
Homo sapiens
Europe
*
bolide impact?
Greenland interstadial onset uncertainties
H1 H2 H3 H4 H5
MIS1 MIS2 MIS3
GI-12
GICC05
Cariaco-GICC05
O
18
Mammuth.pri
Saiga.tat
Megaloceros.gig
Coelod.ant.Rus
Bison.x
Panth.leo.spe
Palaeolox.nau
Ursus.spe.Eur
Croc.croc
Ursus.spe1.Inv
Ursus.spe2
Mammuth.pri.I.Inv
Bison.x.Inv
Bison.pri
Mammuth.pri.III
Coelod.ant.Wra
Coelod.ant.Bri Homo.nea
Ovibos.mos
Bison.pri.Inv
blue labels = Eurasia
Mammut.ame
Mammuth.EBer
Panth.leo.spe
Saiga.tat.EBer
Equus.cab
Cervus.ela.Inv
Arctodus.Ber
Ursus.arc.Inv
Equus.fra
Panth.leo.Ber
Panth.leo.Ber.Inv
= GRIWM
= Terminal AMS
black labels = New World
δ
Fig. 1. Megafaunal transition events and Late Pleistocene climate re-
cords. Major megafaunal transition events (regionwide extirpations or global
extinctions, or invasions, of species or major clades) identified in Late Pleis-
tocene Holarctic megafaunaldata sets through aDNA or paleon tological studies,
plotted on a reconstruction of Northern Hemisphere climate from the GICC05
d
18
O record (black wiggle curve). GICC05 interstadial warming events are shown
with light gray boxes.There is an apparent absence of megafaunal events during
the LGM (blue) and, to a lesser extent, the cold Younger Dryas stadial (YD) and a
marked association with interstadials. Accelerator mass spectrometry (AMS)
radiocarbon dates (red bar T2SD,usingPhase calibrationinOxCal4.1)cal-
ibrated by using the dendrodated IntCal <12,500-year data set (36) and
Cariaco Basin (Hulu Cave) data set for older ages (28,33), or GRIWM-based
estimates of ghost ranges (black bar, 95% confidence interval) are given
for each event (20). Eurasian taxa are shown in blue and New World in black,
with animals facing right representing extinctions and those facing left rep-
resenting invasions (.Inv). The chronologically revised Greenland record, de-
veloped by combining the Cariaco Basin and Greenland ice core records, is
also shown (dark gray wiggle curve) for the period >11.5 ka (because it is
identical with GICC05 until this point) (20). Light pink bars (below) represent
the error margins (1 SD) for the estimated onset of GI events in the published
GICC05 chronology (19,20). Heinrich events (Hx)areshownwithmarineiso-
tope stages (MISx)inlightgrayattop(41). NEA-GS-3b was identified via Atlantic
marine sediment cores and radiocarbon dating (42). Calibrated radiocarbon
ages (midpoints without laboratory dating errors) from mammoth remains in
Eurasia (black circles) andNew World (crosses) are plotted acrossthe bottom o f
the figure to demonstrate the lack of obvious taphonomic hiatus during the
time period analyzed (20). The approximate timing of the first presence of
modern humans in North America (New World) and Europe are shown as
vertical gray dashed lines. Abbreviated taxonomic names, with geographic
area appended where necessary, are given: Arctodus.Ber (Arctodus simus East
Beringia); Bison.pri (Bison priscus Europe); Bison.x (Bison n. sp. Europe);
Cervus.ela (Cervus elephas New World); Coelod.ant.Bri (Coelodonta anti-
quitatis Britain); Coelod.ant.Rus (C. antiquitatis Russia); Coelodonta.ant.Wra
(C. antiquitatis Wrangel Island); Croc.croc (Crocuta crocuta spelaea Europe);
Equus.cab (Equus caballus East Beringia); Equus.fra (E. francisci East Beringia);
Homo.nea (Homo neanderthalensis Europe); Mammuth.pri (Mammuthus
primigenius); Mammut.ame (Mammut americanum); Megaloceros.gig (Mega-
loceros giganteus Western Europe); Ovibos.mos (Ovibos moschatus Beringia);
Palaeolox.nau (Palaeoloxodon naumanni Japan); Panth.leo.Ber (Panthera leo
spelaea Beringia); Panth.leo.spe (P. leo spelaea Eurasia); Saiga.tat (Saiga
tatarica Eurasia); Ursus.arc (Ursus arctos East Beringia); Ursus.spe1 and 2
(U. spelaea Germany); Ursus.spe.Eur (U. spelaea Europe). [Further details of
the geographic region and nature of each megafaunal event are presented in
tables S1 and S2.]
RESEARCH |RESEARCH ARTICLES
We therefore used a D-O event tie-point ap-
proach to combine the calendar-age estimates
obtained from Cariaco Basin (28)withthesame
interstadial events recorded in Greenland to al-
low a direct comparison between radiocarbon
dates and climate change, thereby allowing us to
test the apparent association between megafaunal
extinction or replacement with warming events
(Fig. 1). We find the timing of onsets of inter-
stadial warming events in the two records to be
statistically identical (20), allowing us to use
OxCal 4.1 (34) to combine the two chronologies,
and merged the calendar-dated onset of each
interstadial in Cariaco with the annual layer-
counted interstadial onset and duration from
Greenland to generate a new combined record of
the timing and duration of abrupt and extreme
swings of north Atlantic temperature during the
past 56 thousand years (Fig. 1 and tables S3 and
S4) (20). Our new reconstruction shows that, al-
though all current estimates of the onset of inter-
stadial events in the GICC05 d
18
Orecordarewithin
the errors of our combined Cariaco-Greenland
chronology, the uncertainty surrounding these
transitions is greatly reduced (by 18 to 79%) (Fig.
1, table S3, and figs. S2 and S4).
Testing climate-extinction associations
We used statistical resampling to test the dis-
tribution of megafaunal transitions for random-
ness relative to extreme and abrupt climatic events
(either stadials or interstadials), using both the
existing GICC05 and our new Cariaco-Greenland
chronology (Fig. 1 and table S4) (20). We calcu-
lated the probability that the observed overlap
between climate events and extinction or inva-
sion events might be nonrandom by repeatedly
randomizing the temporal position (but not du-
ration) of the former and, for each iteration, count-
ing the number of times overlap was observed
with the latter. To do this, we used the calibrated
radiocarbon age of the terminal observation of a
clade or taxon (youngest age for extinctions,
oldest for invasions) but also inferred unobserved
temporal (ghost) ranges using the Gaussian-
resampled, inverse-weighted McInerney (GRIWM)
method (20,35), which incorporates both sam-
pling density and dating errors to estimate the
most plausible temporal range of last or first oc-
currence. A nonrandom relationship was observed
between interstadial events and megafaunal tran-
sitions for both the terminal observations and the
GRIWM-based estimates, with statistical power
depending on the number of transitions tested,
but no such nonrandom overlap was detected
for stadials (Fig. 2 and Table 1) (20). A nonran-
dom association is observed despite the uncer-
tainties in the taphonomic, sampling, and dating
processes involved in the data sets, and it is ap-
parent with both the standard published GICC05
record and the new combined Cariaco-Greenland
chronology (Table 1). A correlation can be seen
even when terminal Pleistocene events are dis-
carded to avoid the potential confounding im-
pacts of human colonization (Fig. 2 and Table 1).
The Younger Dryas stadial has also often been
suggested as a prime climatic driver of extinctions
(3,4,22), but even for this event, the obs erv ed ex-
tinction events are distributed much more toward
the preceding interstadial warm period (Fig. 1 and
fig. S7), despite the larger dating uncertainties
caused by radiocarbon plateaus at this time (36).
Interstadial impacts
The onsets of interstadials represent the most
rapid and extreme changes observed in the Late
Pleistocene climate record (Fig. 1) (20), and these
are likely to have caused abrupt shifts in temper-
ature or precipitation (either wetter or drier de-
pending on local environments) away from a
previous relatively stable state. These factors would
have promoted changes in species ranges and dis-
tributions, potentially resulting in regional turn-
over. The local or regional expression of global
climate variation (such as D-O events) is highly
variable (37), and this is consistent with the mega-
faunal transition events being distributed broad-
ly in terms of geography, taxonomy, and age.
This diffuse pattern, along with methodological
limitations used in simple genetic paleodemo-
graphic reconstructions (21), might explain why
correlations with climate events may have been
difficult to detect previously. The lack of extinc-
tions during the LGM is consistent with the
stability of the climate during this period, albeit
cold, in contrast with the large millennial-scale
variability before and after, both of which coin-
cide with high rates of extinctions.
The megafaunal taxa analyzed cover a wide
range of life histories and ecological roles and
include forest and steppe taxa. Many species have
a broad niche (e.g., Ursus arctos,Bison spp., and
Neandertals), making it difficult to classify taxa
into cold- or warm-adapted groups as has pre-
viously been advocated (3,4,38). Furthermore,
the rapid and drastic climate changes associated
with both the onset and the end of interstadials,
followed by new climate regimes, are potentially
sufficient to disrupt populations of taxa across a
604 7 AUGUST 2015 •VOL 349 ISSUE 6248 sciencemag.org SCIENCE
Fig. 2. Randomization tests of the timing of megafaunal transitions with interstadial events.
Graphical representation of the simulation results presented in Table 1. The trend lines (dashed lines) show
that the probability of generating the observed overlaps of megafaunal transition events with interstadials
randomly (P) is inversely related to the numberof events examined, whereas, in contrast, the probabilities for
stadials were all > 0.60 (Table 1) (20). A strong correlation (steep gradient) was observed between mega-
faunal transitions (extinctions or invasion events) and interstadials using both: (Aand B)terminalAMS
14
C
dates and (Cand D) GRIWM estimates (which use a statistical model of extinction times based on a time
series of records).The correlationwas observed by using either the GICC05 (shown) or new combined Cariaco-
Greenland (Table 1 and fig. S6) chronologies. The plotted data are from simulations excluding events with
wide confidence intervals, because inclusion nearly always resulted in a greater chance of overlap being
random [i.e., higher Pvalues; see (20)]. To explore the effect of different combinations of megafaunal-
transition events, we removed certain subsets and repeated the simulations: (i) excluding invasion events
[(B) and (D)]—resulting in lower Pof randomness; (ii) with a constrained-range overlap (red *) applied to
reduce error margins around an event where a rapid replacement by a congeneror conspecific was observed
(20)—producing little difference in the results; and (iii) with post-LGM events from either the New World (○)or
Eurasia (□) only (to remove the potential effects of terminal Pleistocene human-associated impacts)—where
low Pwere observed, but sample-size constraints limited the number of simulations able to detect nonran-
dom interstadial overlap (20). The results of these additional simulations are distributed along most of the
power relationship, suggesting the correlations are not driven by any particular grouped subset of the data.
RESEARCH |RESEARCH ARTICLES
wide range of niches. The effects of high-amplitude
climate change, followed by either stadial or inter-
stadial conditions, are potentially compatible
with previous suggestions that the extirpation of
cold- or open-adapted taxa, such as woolly rhino
and mammoth, occurred during interstadials and
warm-adapted taxa, such as the giant deer, during
stadials like the Younger Dryas (38). However, the
widely dispersed temporal record of the megafau-
nal transitions suggests a markedly individualistic
species response (39), presumably exaggerated by
the localized environmental responses to climatic
shifts (37). Simulations of paleovegetation pat-
terns in the late Pleistocene have emphasized the
importance of the duration and nature of inter-
stadial events and their impact on the growth of
factors, such as forests (40). In contrast, we ob-
serve a more pronounced relationship between
short interstadials (IS 3 to 7) and megafaunal
events, rather than with the longer interstadials,
such as 8 and 12, which might have been ex-
pected to allow larger-scale changes in the extent
and nature of forest cover.
Our results lend strong empirical support to
the hypothesis that environmental changes asso-
ciated with rapid climatic shifts were important
factors in the extinction of many megafaunal
lineages. Indeed, the rapid replacement of local
genetic populations by congeners or conspecifics
(e.g., cave bears, bison, and mammoth) revealed
by aDNA suggests that broader-scale metapopu-
lation structures or processes (e.g., long-distance
dispersal, refugia, and rescue effects across spa-
tially distributed subpopulations) were involved
in maintaining ecosystem stability during the re-
peated phases of sudden climate change in the
Pleistocene Holarctic. If so, human presence could
have had a major and negative impact on mega-
faunal metapopulations by interrupting subpopu-
lation connectivity, especially by concentrating on
regular pathways between resource-rich zones
(1), potentially leaving minimal signs of direct
hunting. By interrupting metapopulation processes
(e.g., dispersal and recolonization), humans could
have both exacerbated regional extinctions brought
SCIENCE sciencemag.org 7AUGUST2015•VOL 349 ISSUE 6248 605
Table 1. Randomization tests of the timing of megafaunal transitions with
major climate events. Randomization tests of the timing of major megafaunal
transitions with either interstadial or stadial events on the existing GICC05 and
new combined Cariaco-Greenland time scales (20). The probabilities of gen-
erating the observed overlaps of extinction or invasion events at random with
interstadials [P(rand) interstadials] and stadials [P(rand) stadials] are shown for
both GRIWM and the phase-calibrated terminal AMS dates, along with prob-
abilities expressed on the complementary log-log scale. The correlation tests
revealed nonrandom overlap relationships between t he number of events, n,and
interstadials for both GICC05 and Cariaco-Greenland time scales. In contrast,
probabilities for overlaps at random with stadial events were >0.6 for both
GRIWM and terminal AMS dates. Simulations producing low probabilities of
generating the pattern of overlaps at random are cumulatively highlighted with
asterisks (P<0.1),inblue(P<0.05),andinred(P< 0.01). The power relation-
ships for correlations with the GICC05 time scale are shown in Fig. 2. Simula-
tions including terminal Pleistocene events from only the New World (NW) or
Eurasia (Eur.) or neither (Pre-LGM) were used to explore the potentially con-
founding influences of human impact. Simulations using extinctions only (Extns)
are indicated. The GICC05 time scale did not include interstadial NEA-GS-3b
(table S3) because it is not detected in ice core records (41).CI, confidence interval.
Events
(Eurasia,
New World)
Extinctions /
Invasions Muskox Wide-CI
species
Constrained
range
overlaps
Number of
events (n)
GRIWM
Number of
events (n)
Te r m i na l
AMS
Interstad
P(random)
GRIWM
Interstad
P(random)
Te r m in a l
AMS
Stadial
P(random)
GRIWM
Stadial
P(random)
Te r m in a l
AMS
Interstad
P(random)
GRIWM
Interstad
P(random)
Te r m in a l
AMS
Stadial
P(random)
GRIWM
Stadial
P(random)
Te r mi n a l
AMS
GICC05 chronology (19, 20) Cariaco-Greenland chronology
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All All ✓✓ ✓ 28 29 0.031
*
0.228 0.801 0.999 0.126 0.220 0.998 0.998
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All All ✓✓ ✗ 28 29 0.109 0.009
*
0.995 0.999 0.470 0.082
*
0.989 0.999
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All All ✗✓ ✓ 27 28 0.024
*
0.020
*
0.974 0.997 0.066
*
0.091
*
0.983 0.996
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All All ✗✗ ✓ 21 27 0.038
*
0.075
*
0.994 0.975 0.252 0.117 0.998 0.995
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All All ✗✗ ✗ 21 27 0.600 0.030
*
0.992 0.999 0.487 0.037
*
0.988 0.999
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All Extns ✓✓ ✗ 24 23 0.296 0.005
*
0.999 0.992 0.396 0.023
*
0.999 0.999
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All Extns ✗✓ ✗ 22 22 0.097
*
0.026
*
0.994 0.974 0.302 0.031
*
0.999 0.999
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All Extns ✗✓ ✓ 22 22 0.107 0.001
*
0.965 0.999 0.023
*
0.069
*
0.999 0.997
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All Extns ✗✗ ✓ 18 21 0.089
*
0.048
*
0.999 0.999 0.131 0.087
*
0.994 0.999
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
All Extns ✗✗ ✗ 18 21 0.249 0.001
*
0.999 0.999 0.287 0.007
*
0.999 0.999
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. All ✓✓ ✓ 22 24 0.018
*
0.230 0.985 0.897 0.414 0.529 0.998 0.914
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. All ✓✓ ✗ 23 24 0.453 0.046
*
0.977 0.999 0.425 0.161 0.996 0.950
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. All ✗✓ ✗ 22 23 0.227 0.088
*
0.962 0.822 0.250 0.164 0.994 0.980
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. All ✗✓ ✓ 22 23 0.040
*
0.105 0.958 0.864 0.019
*
0.245 0.982 0.958
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. All ✗✗ ✓ 16 22 0.122 0.150 0.997 0.855 0.125 0.324 0.981 0.971
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. All ✗✗ ✗ 16 22 0.347 0.042
*
0.996 0.958 0.137 0.022
*
0.986 0.987
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. Extns ✗✓ ✓ 17 17 0.283 0.160 0.999 0.964 0.252 0.116 0.998 0.977
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. Extns ✗✗ ✓ 13 16 0.017
*
0.100
*
0.985 0.991 0.073
*
0.424 0.997 0.959
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Eur. Extns ✗✗ ✗ 13 16 0.159 0.265 0.999 0.987 0.221 0.044
*
0.992 0.997
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
NW All ✓✓ ✗ 23 25 0.335 0.060
*
0.385 0.996 0.354 0.075
*
0.975 0.830
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
NW All ✗✓ ✗ 23 24 0.377 0.014
*
0.977 0.996 0.283 0.099
*
0.621 0.840
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
NW All ✗✗ ✓ 16 27 0.215 0.088
*
0.943 0.960 0.382 0.231 0.775 0.865
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
NW All ✗✗ ✗ 16 27 0.528 0.128 0.919 0.608 0.347 0.055
*
0.883 0.899
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
NW Extns ✗✗ ✓ 13 17 0.034
*
0.041
*
0.848 0.929 0.111 0.124 0.943 0.956
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
NW Extns ✗✗ ✗ 13 17 0.041
*
0.026
*
0.636 0.967 0.094
*
0.061
*
0.986 0.952
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Pre- LGM All ✓✓ ✗ 18 20 0.432 0.993 0.987 0.977 0.958 0.942 0.990 0.682
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Pre- LGM All ✗✓ ✗ 17 19 0.918 0.966 0.999 0.611 0.961 0.879 0.999 0.818
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Pre- LGM Extns ✗✗ ✓ 8 12 0.648 0.763 0.918 0.790 0.641 0.902 0.964 0.679
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
Pre- LGM Extns ✗✗ ✗ 8 12 0.688 0.743 0.999 0.641 0.999 0.944 0.999 0.842
.................................... ....................................................... ..................................................... ....................................................... ....................................................... ........................................................ ......................
RESEARCH |RESEARCH ARTICLES
on by climate changes and allowed them to coa-
lesce, potentially leading to the eventual regime
shifts and collapses observed in megafaunal eco-
systems. The lack of evidence for larger-scale
ecological regime shifts during earlier periods of
the Glacial (i.e., >45 ka) when interstadial events
were common, but modern humans were not, sup-
ports a synergistic role for humans in exacerbating
the impacts of climate change and extinction in
the terminal Pleistocene events.
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ACKNOW LEDGMEN TS
We thank the following museums and curators for their generous
assistance with samples, advice and encouragement: Canadian
Museum of Nature (R. Harington); American Museum of Natural
History (R. Tedford); Natural History Museum London (A. Currant);
Yukon Heritage Centre (J. Storer and G. Zazula); University of
Alaska, Fairbanks (D. Guthrie, C. Gerlach, and P. Matheus), Royal
Alberta Museum (J. Burns); Institute of Plant and Animal Ecology,
RAS Yekaterinburg (P. Kosintsev and A. Vorobiev); Laboratory of
Prehistory, St. Petersburg (V. Doronichev and L. Golovanova);
D. Froese; T. Higham; A. Sher; J. Glimmerveen; B. Shapiro;
T. Gilbert; E. Willerslev; R. Barnett; Yukon miners (B. and
R. Johnson, the Christie family, K. Tatlow, S. and N. Schmidt);
L. Dalen and J. Soubrier for data and assistance. This work was
supported by NSF NESCENT workshop “Integrating datasets to
investigate megafaunal extinction in the late Quaternary.”A.C.,
C.T., B.W.B., and C.J.A.B. were supported by Australian Research
Council Federation, Laureate and Future Fellowships. The new
GICCO5-Cariaco Basin d
18
O record is provided in (20) and also
lodged on the Paleoclimatology Database (National Oceanic and
Atmospheric Administration dataset ID: noaa-icecore-19015).
The previously published radiocarbon data, with original
references, is presented in (20). A.C. and C.T. conceived and
performed research; A.C., C.J.A.B., C.T., and B.W.B. designed
methods and performed analysis; A.C. and C.T. wrote the paper
with input from all authors.
SUPPLEMENTARY MATERIALS
www.sciencemag.org/content/349/6248/602/suppl/DC1
Materials and Methods
Supplementary Text
Figs. S1 to S8
Tables S1 to S4
References (43–54)
27 April 2015; accepted 3 July 2015
Published online 23 July 2015
10.1126/science.aac4315
IMMUNODEFICIENCIES
Impairment of immunity to Candida
and Mycobacterium in humans with
bi-allelic RORC mutations
Satoshi Okada,
1,2
*Janet G. Markle,
1
*†Elissa K. Deenick,
3,4
‡Federico Mele,
5
‡
Dina Averbuch,
6
‡Macarena Lagos,
7,8
‡Mohammed Alzahrani,
9
‡Saleh Al-Muhsen,
9,10
‡
Rabih Halwani,
10
Cindy S. Ma,
3,4
Natalie Wong,
3
Claire Soudais,
11
Lauren A. Henderson,
12
Hiyam Marzouqa,
13
Jamal Shamma,
13
Marcela Gonzalez,
7
Rubén Martinez-Barricarte,
1
Chizuru Okada,
1
Danielle T. Avery,
3
Daniela Latorre,
5
Caroline Deswarte,
14,15
Fabienne Jabot-Hanin,
14,15
Egidio Torrado,
16
§
Jeffrey Fountain,
16
|| Aziz Belkadi,
14,15
Yuval Itan,
1
Bertrand Boisson,
1
Mélanie Migaud,
14,15
Cecilia S. Lindestam Arlehamn,
17
Alessandro Sette,
17
Sylvain Breton,
18
James McCluskey,
19
Jamie Rossjohn,
20,21,22
Jean-Pierre de Villartay,
23
Despina Moshous,
23,24
Sophie Hambleton,
25
Sylvain Latour,
26
Peter D. Arkwright,
27
Capucine Picard,
1,14,15,24,28
Olivier Lantz,
11
Dan Engelhard,
6
Masao Kobayashi,
2
Laurent Abel,
1,14,15
Andrea M. Cooper,
16
¶Luigi D. Notarangelo,
12,29
¶
Stéphanie Boisson-Dupuis,
1,14,15
¶Anne Puel,
1,14,15
¶Federica Sallusto,
5,30
#
Jacinta Bustamante,
1,14,15,28
#Stuart G. Tangye,
3,4
#Jean-Laurent Casanova
1,14,15,24,31
†
Human inborn errors of immunity mediated by the cytokines interleukin-17A and
interleukin-17F (IL-17A/F) underlie mucocutaneous candidiasis, whereas inborn errors of
interferon-g(IFN-g) immunity underlie mycobacterial disease. We report the discovery
of bi-allelic RORC loss-of-function mutations in seven individuals from three kindreds of
different ethnic origins with both candidiasis and mycobacteriosis. The lack of functional
RORgand RORgT isoforms resulted in the absence of IL-17A/F–producing T cells in these
individuals, probably accounting for their chronic candidiasis. Unexpectedly, leukocytes
from RORg- and RORgT-deficient individuals also displayed an impaired IFN-gresponse
to Mycobacterium. This principally reflected profoundly defective IFN-gproduction by
circulating gd T cells and CD4
+
CCR6
+
CXCR3
+
ab T cells. In humans, both mucocutaneous
immunity to Candida and systemic immunity to Mycobacterium require RORg, RORgT,
or both.
Inborn errors of human interleukin-17A
and interleukin-17F (IL-17A/F) or interferon-g
(IFN-g) immunity are each associated with a
specific set of infections. Inborn errors of
IL-17A/F underlie chronic mucocutaneous
candidiasis (CMC), which is characterized by in-
fections of the skin, nails, and oral and genital
mucosae with Candida albicans, typically in the
absence of other infections. Five genetic etiologies
of CMC have been reported, with mutations in
five genes (1,2). Inborn errors of IFN-gunderlie
Mendelian susceptibility to mycobacterial dis-
ease (MSMD), which is characterized by selective
susceptibility to weakly pathogenic mycobacteria,
such as Mycobacterium bovis Bacille Calmette-
Guérin (BCG) vaccines and environmental myco-
bacteria. Eighteen genetic etiologies of MSMD
have been reported, involving mutations of nine
genes (3,4). Only a few patients display both
candidiasis and mycobacteriosis, including some
606 7AUGUST2015•VOL 349 ISSUE 6248 sciencemag.org SCIENCE
RESEARCH |RESEARCH ARTICLES
DOI: 10.1126/science.aac4315
, 602 (2015);349 Science et al.Alan Cooper
turnover
Abrupt warming events drove Late Pleistocene Holarctic megafaunal
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